1. Introduction
Extreme precipitation is one of the most severe natural disasters, leading to enormous economic losses worldwide [
1]. In recent decades, extreme precipitation events have been extensively researched worldwide, such as in China, India, North America, South America, Africa, Europe, and Australia [
2]. The magnitude and frequency of extreme precipitation events are expected to increase in the near future, especially at sub-daily timescales, which may lead to more natural disasters such as riverine floods, flash floods, and landslides [
3,
4]. Compared to a single extreme precipitation event, compound extremes related to floods and droughts may aggravate the influence on the environment and society [
5]. Therefore, it is necessary to thoroughly understand the magnitude, duration, and frequency of extreme precipitation events for the effective design, planning, and management of these systems [
6].
In order to address the challenges of extreme precipitation events, it is necessary to implement ecologically sound and sustainable measures based on scientific information [
7]. In detail, the nature and extent of the extreme precipitation-related indicators need to be further studied [
8]. This research is considered essential for developing management policies and assessing the natural and social impacts of extreme precipitation events. In addition, knowledge about extreme precipitation events is vital for everyday life, as it plays an essential role in the management and the response of emergencies [
9]. Recently, the extreme precipitation events analysis at a particular area has paid considerable attention mainly due to its influences for risk management and hazard assessment, especially related to drought/flood disasters [
10].
The simulation and projection of temperature and extreme precipitation events have been extensively studied worldwide [
11]. Changes in temperature and extreme precipitation events have also been researched in China [
12], in the Caribbean [
13], in the Southern Pacific [
14], and in Africa [
15]. Some scholars have researched extreme events of combinations of precipitation and temperature over the past several years and found that the number of extreme events increased rapidly on a global scale [
16]. Extreme precipitation events also affect precipitation patterns and water balance and accelerate desertification. Therefore, it can profoundly impact ecosystems and human society [
17]. The study shows that analysis based on univariate events that are related to each other may underestimate the risks of compound extremes [
18]. These studies show that, with global climate change and human activities, the risk of extreme precipitation events increases significantly in future periods.
China is a country with vast land territory, which occupies a significant portion of the world. The publication of many scholars shows that China’s climate is highly affected by the East Asian summer monsoon [
19]. Since conditions geographical and meteorological are considerably complex and diverse in China, the changes of the extreme precipitation events have been studied by researchers in recent years [
20], identifying changes in regional extreme precipitation events in order to support disaster prevention and policy development in specific regions. Some researchers provide a valuable tool for calling attention to the local government and contributing to global research by comparing China’s results with those of other parts of the world [
21]. In the past decades, the tendency to increase extreme precipitation has been significant in the middle and lower reaches of the Yangtze River, Western and Southwestern China, and some coastal areas of Southern China. In contrast, the decreasing trend of extreme precipitation appears in the northern regions [
22]. The extent to which the changes in the temperature and precipitation-related indices affects the total amount of extreme precipitation events over China in the present climate has not yet been assessed. Moreover, how will this influence change in the near future over China? The present study addresses these questions by analyzing the observational and model simulation data [
23].
Some scholars have pointed out significant changes in indicators that have characterized the frequency and intensity of extreme precipitation events in the past 10 years [
24]. The research on extreme precipitation events in China mainly aims at the whole country or large areas in the north. However, there is little research on extreme precipitation events in Inner Mongolia. The terrain of Inner Mongolia is complex, spanning Northwest China, North China, and Northeast China from east to west. The uncertainty and variability introduced by the complex terrain can be associated with the significant error in precipitation estimates [
25,
26,
27]. The annual precipitation in this area is small and uneven, mainly concentrated in the summer, resulting in frequent droughts and floods, seriously affecting the production of agriculture and animal husbandry and people’s lives [
28]. Due to global warming, the temperature of the whole region has increased significantly in the past 60 years [
29]. Some researchers have found no significant increase or decrease in the average summer precipitation and annual precipitation extreme events in Inner Mongolia. However, after entering the 21st century, the extreme precipitation events from July to August decreased significantly [
30,
31]. However, previous studies have focused on extreme precipitation changes, and there are few studies on the response to climate change, especially the relationship between extreme precipitation and temperature. Therefore, this work further studies the temporal and spatial variations of extreme precipitation in Inner Mongolia to understand better the impact of global climate change there.
This study aimed to detect the correlation and change trends of temperature and extreme precipitation indicators in Inner Mongolia from 1960 to 2019. The research must help understand the nature of climatic phenomena and assess the changes and impacts of extreme precipitation events on the future climate. The remainder of this paper proceeds as follows: Firstly,
Section 2 provides a comprehensive description of the main characteristics of the study area. Secondly, the materials and methods, the results of the investigation, and a discussion are provided. Finally,
Section 6 summarizes the conclusions obtained from this research.
2. Study Area
Inner Mongolia is located within Eurasia, with a temperate continental climate, across Northeast, North, and Northwest China between 97°12′~126°04′ east longitude and 37°24′~53°23′ north latitude (
Figure 1). It covers an area of about 1.183 million squares kilometers, accounting for 12.3% of China’s land area, and is the third-largest province in China. The topography slopes from northeast to southwest, showing a narrow shape, and most of the whole region belongs to a high prototype geomorphological area. Inner Mongolia is the province with the largest number of neighboring provinces in China, with eight provinces bordering it (Heilongjiang, Jilin, Liaoning, Hebei, Shanxi, Shaanxi, Ningxia, and Gansu Province).
The average elevation of Inner Mongolia is about 1000 m. The highest elevation of Inner Mongolia is 3556 m at the Ho-lan Mountains. Inner Mongolia has a vast territory, high latitude, large plateau area, far away from the sea, and mountains along the border, and the climate is dominated by a temperate continental monsoon climate.
Figure 2 shows the Köppen–Geiger climatic zones of Inner Mongolia. It has the characteristics of less and uneven precipitation, strong wind, and drastic temperature changes.
The annual average precipitation in Inner Mongolia is between 219 and approximately 452 mm (
Figure 3a). The precipitation from May to September, June to September, July to August, and monthly maximum precipitation generally account for about 70%, 60%, 30–80%, and 20–60% of the annual precipitation, respectively. The distribution of precipitation during the year is hugely uneven (
Figure 3b). Inner Mongolia has abundant sunshine and light energy resources, and the annual sunshine hours in most areas are more than 2700 h. The average number of gale days in the year is about 10–40 days, and 70% occur in the spring.
4. Results
It can be shown that the spatial distribution of the mean PRCPTOT in Inner Mongolia during the period from 1960 to 2019 was obtained using Kriging interpolation based on ArcGIS software (ESRI, Redlands, CA, USA) (
Figure 4). The spatial distribution characteristic of the mean PRCPTOT of the stations in Inner Mongolia exhibits an increasing trend from northwest to southeast, and there is a significant gap between the maximum and minimum. The minimum of the mean PRCPTOT is observed at Ejinaqi Station as 35 mm, while the maximum is 509 mm at Xiaoergou Station. The spatial difference of the mean PRCPTOT in Inner Mongolia is affected by climate, latitude, geography, and geomorphology. There is a significant difference in the mean PRCPTOT between the southern and northern foothills of the Yin Mountains. The humid air in the south is blocked by the Yin Mountains, resulting in less rainfall north of the Yin Mountains.
The spatial distribution of the mean wet days in Inner Mongolia during the period from 1960 to 2019 is exhibited in
Figure 5. The minimum of the mean wet days is also observed at Ejinaqi Station as 18 days, while the maximum is 153 days at Aershan Station. Unlike the spatial distribution characteristic of the mean PRCPTOT, the maximum of the mean wet days is concentrated in the northeast of Inner Mongolia. The mean wet days in Southeastern Inner Mongolia is at a low level, but the mean PRCPTOT is at a high level, which leads to a higher mean SDII more prone to extreme precipitation events.
The spatial distribution of the mean SDII in Inner Mongolia during the period from 1960 to 2019 is exhibited in
Figure 6. The minimum of the mean SDII is also observed at Ejinaqi Station as 1.93 mm/day, while the maximum is 5.99 mm/day at Zhalute Station. The variation trend of the spatial distribution of the mean SDII is consistent with that of the spatial distribution of the mean PRCPTOT, and the maximum of SDII in Southeastern Inner Mongolia proves the previous inference. Similarly, there is a significant difference in the mean SDII between the southern and northern foothills of the Yin Mountains. Under the influence of the monsoon, the moist air reaching the southern foothill of the Yin Mountains is lifted by the terrain during air movement. With the increase of altitude, the water vapor cools to form precipitation, making the precipitation at the southern foothill of the Yin Mountains higher than the northern foothill of the Yin Mountains.
In order to understand the essential characteristics of the study data, descriptive statistics (
Table 2) provide the standard deviation; minimum, maximum, and mean for temperature; and other extreme precipitation indicators. Overall represents that all the statistical data of 2100 observations are used for calculation. Between represents that the results are calculated based on the statistical data of 35 stations regardless of time. Within represents that the results are calculated using the statistical data of 60 years regardless of stations.
The concepts of “spurious regression” and “spurious correlation” could appear between independent unit root variables. Therefore, for panel data, we should first carry out a unit root test for each variable in the panel—that is, the stationarity test of variables. The method of the unit root test mainly included the LLC unit root test, IPS unit root test, Breitung unit root test, and Fisher unit root test. In order to ensure the reliability of the conclusions, this study comprehensively used the above four methods to test the stationarity of the temperature and other extreme precipitation indicators and then judged the stationarity of the variables (
Table 3). The research showed that all variables were stationary sequences at the significance level of 5%, and all sequences contained drift terms and trend terms.
The optimal lag order is selected by the MBIC, MAIC, and MQIC. In the study, the optimal lag order of the model is selected to be 5 using Stata software. According to the test of the eigenvalue stability condition of the model, it was found that all eigenvalues of the PVAR models were inside the unit circle, indicating that the PVAR models had a high degree of stability. The paper researched the Granger cause equation between temperature and other extreme precipitation indicators. The results showed that all H
0 were rejected besides the fact that SDII is not a Granger cause Equation variable (
Table 4). Therefore, the research shows Granger reasons between temperature and other extreme precipitation indicators. That is, the temperature will exert influence on the extreme precipitation indicators.
According to the correlation matrix of all the study variables (
Table 5), the temperature had a positive correlation with only SDII and a negative correlation with the remaining variables. It was also found from the correlation matrix that all study variables were correlated at the significance level of 1%. It represented a highly negative correlation of the correlation coefficient of the temperature and wet days over 0.7.
The study shows the MK trend test distributions of all variables from 1960 to 2019 (
Table 6). The temperatures at all stations showed significant increasing trends, and there is no doubt that the climate is gradually warming. We were surprised to find that the PRCPTOT of almost all stations exhibited no significant trend, and only Manzhouli was detected to have a decreasing trend. According to the above correlation matrix results, it is inferred that the PRCPTOT in Inner Mongolia may show a downward trend in the future. The wet days of most stations also exhibited no significant trend, and only the wet days of one out of five stations were detected to have a decreasing trend. Interestingly, most of these stations were located in the eastern part of Inner Mongolia. The SDII of seven stations detected a significant increasing trend, but two stations exhibited a decreasing trend, which was worthy of further study, and the rest stations showed no significant trends. In a word, the SDII of some stations were detected to have increasing trends, and it can be indicated that the extreme precipitation events are increasingly severe.
5. Discussion
The spatial distribution of the extreme precipitation indicators (PRCPTOT, Wet Days, and SDII) in Inner Mongolia tends to be maximum in the southeast and minimum in the northwest. The results are consistent with the research in Inner Mongolia publicized by other scholars [
53].
The research used panel data and a time–series data analysis technique to test the general theory by examining the correlation between the temperature and three extreme precipitation-related indicators in the past. The previous research suggests that extreme precipitation events have become increasingly severe with global warming [
54,
55]. Therefore, we detect causality for temperature and extreme precipitation indicators PRCPTOT, Wet Days, and SDII. Our findings suggest that the decreasing trend in PRCPTOT and wet days is accompanied by increases in the temperature. In contrast, the other type of relationship exhibited an increasing trend in SDII with increasing temperature. A station with the first relationship between PRCPTOT and temperature means an increased risk of drought or/and flood disaster events at the station. In addition, the station of the first relationship between PRCPTOT and temperature occurred in Northeastern Inner Mongolia. The climate characteristics of Inner Mongolia are very dry, and the annual precipitation is relatively small. Therefore, there is a greater risk of drought for the stations that showed the first type of relationship between PRCPTOT and temperature in the dry season. Due to the small wet days, the more concentrated the rainfall, the more flood disasters are caused. The second relationship between SDII and temperature means that flood disasters are becoming more and more frequent. Therefore, flood prevention should be paid attention to at some stations, such as Tulihe, Xiaoergou, and Chifeng.
Regarding temperature and extreme precipitation-related indicators from 1960 to 2019, PRCPTOT and wet days were mainly observed in decreasing trends across Inner Mongolia. Some scholars showed that the increasing trends of PRCPTOT aggravate the hazard of flooding, because a large amount of precipitation indicates an incidence of torrential rain. On the contrary, the decreasing trend of PRCPTOT indicates that more dry periods could be detected [
56]. However, SDII has shown a significant increasing trend in some stations in Inner Mongolia, such as Tulihe, Xiaoergou, and Aershan, which indicates that we should pay attention to the growing number of extreme precipitation events. At the same time, the present study shows that the decline rate of PRCPTOT in most stations was not as fast as that of wet days, which proves once again that extreme precipitation events are becoming more and more frequent. For temperature, all stations observed significant increasing trends in line with the current global warming situation. Some scholars suggested that changes in extreme climate events in most parts of the world are amplified at the tails, such as increases in extremely high temperatures, decreases in extremely low temperatures, and increases in extreme precipitation events [
10]. In summary, the extreme precipitation events in Inner Mongolia have exhibited increasing trends, but precipitation is detected in decreasing trends.
The reduction of precipitation will significantly affect the ecosystem, the hydrological cycle, and the water supply of society. In detail, changes in precipitation will cause changes in runoff and groundwater to affect the hydrological cycle, which, in turn, affects the water supply and ecological environment. For agriculture, one of the most critical industries in China, the reduction of precipitation leads to a lack of soil moisture, greatly influencing crops. As far as hydropower projects are concerned, the influence of runoff change is very critical. In addition, the changes in extreme precipitation events are particularly significant for managing water resources, the formulation of flood control policies, the reduction of soil erosion, and the acquisition of natural water resources [
57,
58]. Ultimately, the changes of extreme precipitation events will significantly influence the ecosystem and human society of the whole of Inner Mongolia.